Stimulation channel selection methods

ABSTRACT

Stimulation channel selection methods for an implantable neural stimulation system having a multiplicity of channels include computing a probability for each channel within the multiplicity of channels and selecting at least one of the channels for stimulation during a frame. The selecting of the at least one of the channels for stimulation during the frame includes selecting a channel, obtaining a random number, comparing the random number to the probability of the channel, and selecting the channel for stimulation if the probability of the channel is greater than the random number.

RELATED APPLICATIONS

The present application is a continuation application of U.S.application Ser. No. 10/318,433, filed Dec. 13, 2002 now U.S. Pat. No.7,130,694, which application claims the benefit of ProvisionalApplication Ser. No. 60/344,639, filed Dec. 26, 2001 and its Appendix.Both applications, including the Appendix of Provisional ApplicationSer. No. 60/344,639, are incorporated herein by reference in theirentireties.

BACKGROUND

Hearing loss may be due to many different causes, but is generally oftwo types: conductive and sensorineural. Of these, conductive hearingloss occurs where the normal mechanical pathways for sound to reach thehair cells in the cochlea are impeded, for example, by damage to theossicles. Conductive hearing loss may often be helped by use ofconventional hearing aids, which amplify sound so that acousticinformation, in the form of pressure waves, reaches the cochlea and thehair cells. Some types of conductive hearing loss are also amenable toalleviation by surgical procedures.

In many people who are profoundly deaf, however, the reason for theirdeafness is sensorineural hearing loss. This type of hearing loss is dueto the absence or the destruction of the hair cells in the cochlea whichare needed to convert acoustic signals into auditory nerve impulses.People with sensorineural hearing loss are unable to derive any benefitfrom conventional hearing aid systems, no matter how loud the acousticstimulus is made, because their mechanisms for converting sound energyinto auditory nerve impulses have been damaged. Thus, in the absence ofproperly functioning hair cells, auditory nerve impulses are notgenerated directly from sounds.

To overcome sensorineural deafness, numerous Implantable CochlearStimulation (ICS) systems—or cochlear prosthesis—have been developed.Such systems seek to bypass the hair cells in the cochlea by presentingelectrical stimulation to the auditory nerve fibers directly, leading tothe perception of sound in the brain and at least a partial restorationof hearing function. The common denominators in most ICS systems havebeen the implantation of electrodes into the cochlea, and a suitableexternal source of an electrical signal for the electrodes.

An ICS system operates by direct electrical stimulation of the auditorynerve cells, bypassing the defective cochlear hair cells that normallyconvert acoustic energy into electrical activity in the nerve cells. Inorder to effectively stimulate the nerve cells, the electronic circuitryand the electrode array of the ICS system perform the function ofseparating the acoustic signal into a number of parallel channels ofinformation, each representing the intensity of a narrow frequency bandwithin the acoustic spectrum. Ideally, the electrode array would conveyeach channel of information selectively to the subset of auditory nervecells that normally transmit signals within that frequency band to thebrain. Those nerve cells are arranged in an orderly tonotopic sequence,from high frequencies at the basal end of the cochlear spiral toprogressively lower frequencies towards the apex, and ideally the entirelength of the cochlea would be stimulated to provide a full frequencyrange of hearing. In practice, this ideal is not achieved, because ofthe anatomy of the cochlea which decreases in diameter from the base tothe apex, and exhibits variations between patients. Because of thesedifficulties, known electrodes can at best be promoted to the secondturn of the cochlea.

The signal provided to the electrode array is generated by a signalprocessing element of the ICS system. In known ICS systems, the acousticsignal is processed by a family of parallel Bandpass (BP) filters, orthe equivalent, resulting in M stimulation channels. Generally, theimportant information for speech understanding is contained in subset ofall the M channels. This subset is usually made up of the channelscontaining the highest amplitude signals among the M channels at anygiven time. One common stimulation strategy selects N of the M channelsfor stimulation based on the amplitude of the signals in the channels.There are at least two advantages to the N out of M (N-of-M) strategy.First, an N-of-M strategy allows higher stimulation rates for a givenpulse width when using non simultaneous stimulation. Second, an N-of-Mstrategy performs a data reduction function, in that BP channels thatcontain lower amplitude information are effectively muted, limitingtheir contribution to electrode interaction problems.

But, there are potential disadvantages to N-of-M strategies as well. Thedata reduction function of a standard N-of-M strategy is implementedusing an all or nothing algorithm, selecting only the channels with thehighest amplitude signals in a given stimulus frame. This means that allinformation in the lower amplitude channels is lost during that frame.This could be very disadvantageous in situations where the overallfrequency distribution remains relatively constant for a period of time,such as when listening in certain noisy environments or detectingbackground sounds during vowels. One example of this would be someonehonking a horn while someone is talking. If the horn is loud enough, itsspectral content would overwhelm the talker, and the standard N-of-Mdecision matrix would only deliver envelope information to the pulsegenerator for those channels which contain “horn content”. All of theother channels would be effectively muted.

What is needed is a method for processing the channels of an ICS system,which method provides the advantages of an N-of-M stimulation strategy,without muting channels having low to moderate signal amplitudes.

SUMMARY

Stimulation channel selection methods for an implantable neuralstimulation system having a multiplicity of channels include computing aprobability for each channel within the multiplicity of channels andselecting at least one of the channels for stimulation during a frame.The selecting of the at least one of the channels for stimulation duringthe frame includes selecting a channel, obtaining a random number,comparing the random number to the probability of the channel, andselecting the channel for stimulation if the probability of the channelis greater than the random number.

BRIEF DESCRIPTION OF THE DRAWINGS

The above and other aspects, features and advantages of the presentsystems and methods will be more apparent from the following moreparticular description thereof, presented in conjunction with thefollowing drawings wherein:

FIG. 1 shows the major elements of a known Implantable CochlearStimulation (ICS) system;

FIG. 2 shows a block diagram of the N out of M (N-of-M) processing;

FIG. 3 depicts a plot of channel probability versus channel number,arranged by decreasing probability;

FIG. 4 shows a flow chart for a probabilistic N-of-M channel selectionmethod;

FIG. 5 shows a flow chart for an adjustable threshold based N-of-Mchannel selection method;

FIG. 6 graphically depicts a mapping from an amplitude to aprobability-of-selection for a combination of probability and thresholdbased N-of-M channel selection method;

FIG. 7 shows a flow chart for the combination probability and thresholdbased N-of-M channel selection method; and

FIG. 8 shows a flow chart of a second embodiment for the combinationprobability and threshold based N-of-M channel selection method.

Corresponding reference characters indicate corresponding componentsthroughout the several views of the drawings.

DETAILED DESCRIPTION

Improved pulse skipping strategies for implantable neural stimulationsystems are described herein. In some examples, the methods and systemsdescribed herein select N out of M (N-of-M) channels for stimulationduring a stimulation frame. A microphone transduces acoustic energy intoan electrical signal. The electrical signal is processed by a family ofbandpass filters, or the equivalent, to produce M frequency channels. Inan exemplary embodiment, a probability based channel selection strategycomputes a probability for each of the M channels based on the envelopeamplitude of the signal on each channel. N of the M channels areprobabilistically selected for stimulation based on their individualprobability. The result is a randomized “stochastic” stimuluspresentation to the patient.

In the following description, for purposes of explanation, numerousspecific details are set forth in order to provide a thoroughunderstanding of the present systems and methods. It will be apparent,however, to one skilled in the art that the present systems and methodsmay be practiced without these specific details. Reference in thespecification to “one embodiment” or “an embodiment” means that aparticular feature, structure, or characteristic described in connectionwith the embodiment is included in at least one embodiment. Theappearance of the phrase “in one embodiment” in various places in thespecification are not necessarily all referring to the same embodiment.

In accordance with one aspect of the present methods and systems, thereis provided a probability based N-of-M stimulation strategy. Suchrandomized stimulation advantageously reduces “under representation” ofweak channels for steady state input conditions, such as vowels.

In some examples, the present methods and systems provide more naturalstimulation to the user. Naturally occurring nerve firing patterns tendto exhibit random behavior. Randomizing the selection of channelsproviding stimulation better matches the naturally occurring patterns.Further, random selection of channels tends to eliminate adverse effectsthat result from a more strictly periodic stimulus, such as the tendencyfor certain patients to detect the carrier.

The methods and systems described herein also provide a capability toemphasize specified channels. For example, when a transient condition isdetected, channels carrying high frequency signals may be given apreference in the N out of M selection process, thereby emphasizing thehigh frequency content of the transient. Parameters of the transientdetection process and the selection criteria of high frequency channelsmay be tuned to a particular user during ICS fitting.

The methods and systems described herein also reduce processingrequirements compared to known bubble sorting methods. A runningthreshold is maintained. At each stimulation frame, the amplitude ofeach channel is compared to the threshold, and channels with amplitudesexceeding the threshold are selected for stimulation. A variable “J” isset to the number of channels selected. The threshold is increased if“J” is greater than N, and the threshold is decreased if “J” is lessthan N, thus controlling the number of channels selected. Because thistechnique does not use an expensive bubble sort operation, it savesprocessor resources, which extends the battery life of the SCS system.

The present methods and systems relate to multi-channel implantableneural stimulation systems, and more particularly to a probabilistictechnique for selecting which channels of the multi-channel neuralstimulation system are to be selected for providing stimulation based ona given input signal. While the present methods and systems aredescribed in connection with an implantable cochlear stimulation (ICS)system, it is to be understood that the present methods and systems isnot limited for use only in ICS systems. Rather, the present methods andsystems may find applicability in many types of neural stimulationsystems where multi-channel stimulation is provided, including spinalcord stimulation systems, deep brain stimulation systems, and otherneural stimulation systems.

An exemplary probabilistic pulse skipping strategy for ImplantableCochlear Stimulation (ICS) systems selects N out of M (N-of-M) channelsfor stimulation during a given stimulation frame. A functional diagramof a typical ICS system is shown in FIG. 1. The ICS system includes aspeech processor 10 that could be a Wearable Speech Processor (WP), aBehind-The-Ear (BTE) speech processor, an implantable speech processorof a fully implantable cochlear stimulation system, or any signalprocessor that is used to process acoustic signals for use by an ICSsystem. By way of overview, a microphone 12 is electrically connected toa speech processor 10 by a first wire 14, or may be attached to thespeech processor 10 as in the case of known BTE speech processors. Themicrophone 12 may also, in some embodiments, be coupled to the speechprocessor 10 via a wireless link.

The microphone 12 converts acoustic energy into an electrical signal forsubsequent processing. The speech processor 10 contains a signalprocessor 16 that processes the electrical signal from the microphone12. The output signal of the signal processor 16 is carried by a secondwire 18, or equivalent link, to a headpiece 20 carried on the patient'shead. A first (or primary) coil 22 receives the output signal andtransmits it as a control signal 24 from the headpiece 20 to implantableelectronics 28. The implantable electronics 28 include a second (orsecondary) coil 26 for receiving the control signal 24.

The implantable electronics 28 processes the control signal 24 andderives therefrom the information needed in order to generate astimulation current that is provided through a lead 30 to one or more ofelectrodes of the electrode array 32. The electrode array 32 comprises amultiplicity of electrodes. The electrode array 32 is implanted in thepatient's cochlea.

The architecture of ICS systems may vary. The ICS system may include awearable speech processor that is worn on the users belt and isconnected to a microphone and a headpiece by wiring, or a Behind-The-Ear(BTE) speech processor resembling a typical hearing aid, that is wornbehind the patient's ear and retained by an earhook. Another example isa fully implantable ICS system in which a speech processor 10 isintegrated into an implantable device. Those skilled in the are willrecognize that all of these variations include similar signalprocessing, and that all of these variations benefit from the presentmethods and systems, as described below, and are intended to come withinthe scope of the present methods and systems.

A functional block diagram of an ICS system that includes an N out of Mpulse skipping strategy is shown in FIG. 2. The microphone 12 isconnected by the first signal path 14 to an Automatic Gain Control (AGC)circuit 32 in the signal processor 10. The output 34 of the AGC circuitis input to M Bandpass Filters (BPF) 36 a-36 m having output channels 38a-38 m. The BPF output channels 38 a-38 m are input to respectiveenvelope detector circuits 40 a-40 m. The BPF output channels 38 a-38 m,and the envelope output signals 42 a 42 m, are provided to processingcircuitry 44 that selects N out of M channels. TheSelect-N-out-of-M-Channels circuit 44 thus provides N channels selectedfor stimulation, 46 a-46 n, to a Pulse Generator 48. Leads 50 a-50 mrespectively connect electrodes 52 a-52 m to the Pulse Generator 48.However, stimulation signals are present only on N of the M leads, whichN leads correspond to the N channels selected for stimulation 46 a-46 n.

The functional diagram in FIG. 2 includes functions that may be used inthe pulse skipping strategy. Those skilled in the art will recognizethat the signal processor typically performs other signal processingfunctions not shown (e.g., compressive mapping, determination andprovision of power, etc.). A more complete description of the mainfunctions performed by a typical ICS system may be found in U.S. Pat.Nos. 6,219,580 and/or 6,308,101, both of which patents are incorporatedherein by reference. Moreover, those of skill in the art will appreciatethat the functional block diagram of FIG. 2 illustrates just onearchitecture—dividing the incoming signal into frequency bands, andprocessing each band in parallel—that may be used in a cochlear implantsystem. The present methods and systems are not limited to sucharchitecture, but rather relates to the way N of M channels areselected, e.g., to the function that is carried out in the “Select N ofM Channel” box 44 shown in FIG. 2. The circuitry that precedes andfollows the box 44 is not central to the present methods and systems,and may be achieved in numerous ways.

A first embodiment of an improved pulse skipping strategy includes theuse of a discrete probability function. An example of a probabilityfunction for a strategy where N=6 and M=16 is shown in FIG. 3. Theprobabilities of the 16 channels are scaled so that the sum of theprobabilities of the 16 channels is 6. As a result, the averageprobability in this example is 6/16. The 16 channels are compared torandom numbers from a uniform distribution between zero and one, onechannel at a time. For example, if a channel has a scaled probability of0.85, and the random number provided for the comparison is less than0.85, the channel will be selected for stimulation (i.e., the channelwill be selected 85% of the time.) Similarly, a channel with aprobability of 0.10 will be selected 10% of the time. The random numbersare unique for each comparison, and may be obtained through tablelook-up, a random number generator, or from some other method ofobtaining random numbers. Any method of obtaining the random numbers maybe used.

Channel selection is complete when N channels (6 channels in theexample) have been selected for stimulation for a given frame. The orderin which the probabilities of the channels are compared to a randomnumber may be randomized to provide an opportunity for low probabilitychannels to be selected, or some other method of determining an orderfor channel selection may be utilized.

A flow chart of the steps comprising the probabilistic pulse skippingstrategy described above is shown in FIG. 4. In FIG. 4, each main stepof the strategy is represented as a “block”, having a reference number.As seen in FIG. 4, the M channel signals for a frame are received (block54). There is an amplitude associated with each of the M channelsignals. One of the M channels is selected for further processing (block60). In some examples, a method for picking a channel is utilized thatallows representation of all channels, e.g., the channels may beselected randomly. A probability “P” for the picked channel is thencomputed (block 62) as described above in connection with FIG. 3. Forexample, the probability may be computed as N/M weighted by theamplitude of the signal. A random number “R” is also generated (block64), as also described above in connection with FIG. 3. A determinationis then made as to whether “P” is greater than “R” (block 66).

If the probability “P” is less than the random number “R”, then thatchannel is not selected as one of the N channels selected forstimulation during the frame (block 68). A new channel is then picked(block 60) and the process of computing a probability “P” (block 62) andproviding a random number “R” (block 64) and comparing the probability“P” of the selected channel to the random number “R” (block 66) isrepeated.

If the probability “P” is greater than the random number “R”, then thatchannel is selected to be one of the N channels selected for stimulationduring the frame (block 68).

A determination is next made as to whether N channels have been selected(block 70) for stimulation during the frame. If less than N channelshave been selected for stimulation, a new channel is picked (block 60)and the process of computing a probability “P” (block 62) and providinga random number “R” (block 64) and comparing the probability “P” of theselected channel to the random number “R” (block 66) and selecting thechannel for stimulation (bock 68) is repeated. When N channels have beenselected for stimulation, the process is complete, and stimulation maybe provided (block 72).

There are at least two differences between a probabilistic pulseskipping N-of-M strategy and known N-of-M strategies. First, considerthe situation where the dominant spectral cues are completely static (anexample of this would be someone honking a horn while someone istalking). If the dominant static spectral cues are loud enough (i.e., ifthe horn is loud enough), the spectral content of the static cues wouldoverwhelm the talker, and the standard N-of-M decision matrix would onlyselect channels for stimulation that contain the dominant staticspectral cues, i.e., that contain “horn content”. All of the otherchannels would be effectively muted. However, when the probabilityfunction of the random pulse skipping N-of-M strategy of the presentmethods and systems are employed, the weaker channels would stilldeliver stimulus to the patient, albeit at a lower rate than the strongchannels. This is a substantial advantage in certain listeningenvironments, especially noisy environments.

Second, the random pulse skipping N-of-M strategy of the present methodsand systems randomizes the stimulus to any channel to a certain extent.Randomized stimulus may be more natural in that is it similar to nervefiring patterns that occur naturally. Also, a randomized stimulus tendsto eliminate adverse effects that result from a more strictly periodicstimulus, such as the tendency for certain patients to detect thecarrier.

The randomization shown in FIG. 3 is not as pronounced as it might be.If the distribution of the firing probabilities were flatter, therewould be more randomization and less channel reduction (less emphasis ofthe strong spectral channels). However, if N is lowered, and the FiringProbability Curve linearly adjusted to reflect this, the randomizationis increased without affecting the extent of the channel reduction. Ncan be lowered without under representing the bulk of the stimuluschannels. The result is a highly randomized stimulus that represents allthe channels, yet emphasizes the stronger ones.

In a second embodiment of the present methods and systems, a relativelysimple alternative to known N-of-M strategies is utilized that comprisescomparing the channel signal amplitudes with a first threshold. In eachframe, all the amplitudes are compared with the first threshold.Channels with amplitudes above the first threshold are selected forstimulation. The first threshold is not constant, and may be adjustedafter every frame. If more than N channels are above the first thresholdin a frame, the first threshold used for the next frame is raised by acertain amount. If less than N channels are above the first threshold,the first threshold used for the next frame is lowered by a certainamount. In this way, the first threshold is dynamically adjusted to apoint where an average of N channels will be selected for stimulationper frame.

However, because there is no guarantee that exactly N channels will meetthis criteria during any given frame, a method is required to adjust thechannel selection so that N channels are selected. There are many waysto ensure that exactly N channels are selected for stimulation. If morethan N channels are initially selected for stimulation, high frequencyor low frequency channels may be given precedence when selectingchannels (for example, selecting the N highest frequency channels thatexceed the first threshold, or selecting the N lowest frequency channelsthat exceed the first threshold). Alternatively, channels may berandomly de-selected from the group of channels that exceed the firstthreshold, until a total of N channels remain selected for stimulation.As another approach, when the number of channels selected forstimulation for a given frame far exceeds the number N, the channels maybe sorted by amplitude. Sorting by amplitude in these limited caseswould give a more conventional result, while generally only requiring asort during transients.

In the case where less than N channels exceed the first threshold,additional channels may be selected from the channels with amplitudesthat failed to exceed the first threshold based on frequency (forexample, selecting the additional channels from the highest frequencychannels with amplitudes that failed to exceed the first threshold, orselecting the additional channels from the lowest frequency channelsthat failed to exceed the first threshold.) Alternatively, additionalchannels may be randomly selected from the channels with amplitudes thatfailed to exceed the first threshold, until a total of N channels areselected for stimulation.

A flow chart of the second embodiment of the present methods and systemsis shown in FIG. 5. As a first step, the channel signals for the frameare received (block 80). A first threshold is then provided (block 82),which may be either a stored initial value of the first threshold, or avalue of the first threshold recursively computed (e.g., at blocks 90 or96, as explained below). Next, the channels having an amplitude greaterthan the first threshold are selected for stimulation (block 84). Aparameter “J” is then set to be equal to the number of channels selected(block 86). A determination is then made as to whether “J” is greaterthan “N” (block 88). If more than “N” channels were selected forstimulation, the first threshold is increased (block 90) for the nextframe, and channels are de selected to reduce the total number ofchannels selected for stimulation to the number “N” (block 92).Exemplary methods for increasing the threshold, and for choosingchannels to de-select, may be as described above.

If “J” is smaller than “N” (block 94), then a determination is made todetermine if less than “N” channels were selected for stimulation. Ifless than “N” channels were selected for stimulation, the firstthreshold is decreased (block 96) for the next frame, and additionalchannels are selected until “N” channels have been selected (block 98).Exemplary methods for decreasing the threshold, and for choosingadditional channels to select for stimulation, may be as describedabove.

Stimulation is then provided on the “N” channels that have been selected(block 100).

A third embodiment of an improved pulse skipping strategy in accordancewith the present methods and systems combines a probability based pulseskipping strategy and a second threshold based pulse skipping strategy.In accordance with this embodiment, an adjusted amplitude is computedfor each channel by subtracting a second threshold (in dB) from theamplitude (in dB) of each channel. The adjusted amplitude is mapped intoa probability based on the mapping shown in FIG. 6. The greater theadjusted amplitude (in dB), the higher the probability of the channelwill be, and the more likely it is that the channel will be selected forstimulation during the frame. As a result, there is no “yes-or-no”decision about whether to select the channel as in the secondembodiment, and there is no discontinuity in the selection function.Channels with amplitudes that are significantly higher than the secondthreshold will be proportionally more likely to be selected forstimulation.

A flow chart of the third embodiment is shown in FIG. 7. As seen in FIG.7, for each frame of data, the channel signals are received (block 110).A second threshold is next provided (block 112) that is either a storedinitial value of the second threshold, or the second thresholdrecursively computed (as explained below). A loop is then entered whichis executed once for each channel. Upon entering the loop, a channel ispicked (block 114) that has not been tested for selection during thepresent frame. The picked channel includes an amplitude, which iscomputed as one of several possible measures of the amplitude of thesignal on the picked channel, and may include an envelope signal. Anadjusted amplitude is then computed (block 116) as the amplitude of thepicked channel minus the second threshold (in dB). The adjustedamplitude is then mapped into a probability “P” (block 118) using anappropriate mapping scheme, such as the mapping relationship shown inFIG. 6. A random number “R” is then provided (block 120), e.g., bylooking up a random number in a table, by generating a random numberusing a random number generator, or by some other means. Such randomnumber is uniformly distributed between zero and one.

Still with reference to FIG. 7, a determination is next made as towhether “P” is greater than “R” (block 122). If the probability “P” isgreater than the random number “R”, the picked channel is selected forstimulation (block 124), and a determination is made as to whether all“N” channels have been selected (block 126). If (at block 122) theprobability “P” is not greater than the random number “R”, then anotherchannel is picked (block 114) for testing and the loop begins again. Theabove-described loop (comprising blocks 114-126) is then repeated asrequired until “N” channels have been selected for stimulation.

Continuing with FIG. 7, once N channels have been selected forstimulation, the second threshold may be adjusted, if necessary. This isdone by computing the adjusted amplitudes for all channels (block 128),and then mapping the adjusted amplitude into a set of probabilities P(block 130), as was done previously (at blocks 118 and 120). Next, arounded sum “S” of the probabilities is computed (block 132) by summingthe probabilities, and rounding the sum to nearest integer. Adetermination is then made as to whether the rounded sum “S” is greaterthan “N” (block 134), and if so, the second threshold is increased(block 136). Similarly, a determination is made as to whether therounded sum “S” is less than “N” (block 138), and if so, the secondthreshold is decreased (block 140). Once the second threshold has beenadjusted, either increased (block 136) or decreased (block 140), thestimulation is provided on the selected “N” channels (block 142).

A flow chart of a fourth embodiment of the present methods and systemsis illustrated in FIG. 8. The fourth embodiment utilizes the samemapping of a signal amplitude in dB into a probability as used in thethird embodiment, but exercises a different channel selection process.As seen in FIG.8, channel signals for the current frame are received(block 150). A third threshold is provided (block 152), which thirdthreshold may be either a stored initial value, or a third thresholdrecursively computed, as explained below. A loop is then entered whichis executed once for each channel. In the loop, an untested channel isselected (block 154). The picked channel includes an amplitude, whichmay be computed as one of several possible measures of the amplitude ofthe signal on the picked channel, and may include an envelope signal.The amplitude of the picked signal is then adjusted (block 156). Theadjusted amplitude may be computed as the channel amplitude minus thethird threshold. The adjusted amplitude is then mapped (e.g., by usingthe mapping shown in FIG. 6) into a probability “P” (block 158). Then, arandom number “R” is provided (block 160). The random number may bederived from a random number look up table, or may be generated usingany other appropriate means. The random number should be uniformlydistributed between zero and one.

Next, a determination is made as to whether “P” is greater than “R”(block 162). If not, a new untested channel is selected (block 154) andthe loop begins again. If “P” is greater than “R”, then the pickedchannel is selected for stimulation (block 164). A determination is thenmade as to whether all “M” channels have been tested (block 166),thereby assuring that all of the channels have had an opportunity to beselected for stimulation. If not, then the loop begins again (at block154) for each untested channel.

After all of the channels have had an opportunity to be selected forstimulation, further processing is performed to ensure that exactly Nchannels are selected, and to adjust the third threshold if more or lessthan N channels have been selected. To do this, a parameter “J” is setequal to the number of channels selected for stimulation (block 168) anda determination is made as to whether J is equal to “N”, the number ofchannels that should be selected for stimulation in the frame (block170). If “J” is greater than “N”, then more than “N” channels wereselected for stimulation, and the value of the third threshold isincreased (block 172) for use in subsequent frames. Channels are then deselected to reduce the total number of channels selected for stimulationto the number “N” (block 174). The methods for increasing the thirdthreshold, and for choosing channels to de-select, may be the same asthose described in connection with the second embodiment above.

If “J” is less than “N” (block 176), then fewer than “N” channels wereselected for stimulation, and the value of the third threshold isdecreased (block 178) for use in subsequent frames. Additional channelsare then selected to increase the total number of channels selected forstimulation to the number “N” (block 180). The methods for decreasingthe third threshold, and for choosing additional channels to select forstimulation, may be the same as those described above in connection withthe description of the second embodiment. Stimulation is then providedon the selected channels (block 182).

In the manner described above, and as shown in FIG. 8, the thirdthreshold is recursively adjusted, either by increasing its value (block172), or by decreasing its value (block 178).

It is noted that the second and fourth embodiments described above mayhave useful effects during transients, such as would occur duringconsonants in speech. By modifying the channel selection criteria,certain channels may be emphasized under these conditions. For example,if preference is given to high frequency channels when more than Nchannels are above the threshold, the high frequency content oftransients will be emphasized. This is in contrast to the probabilisticselection process of the first and third embodiments described above,which tend to emphasize all of the input channels equally during atransient. Using either of these approaches during transients mayimprove hearing, and the results will vary depending on the particularpatient. These and other methods may be explored during the patientfitting process, and the methods that provide the best performance canbe programmed into the ICS system for each patient.

Much is known about human hearing and its non-linear behavior. Humanhearing is known to be more sensitive to certain frequency ranges, andit is known that the sensitivity curves may change with volume. Thereare many frequency and time-based masking effects. Much of this behaviormay be incorporated into the selection of channels for stimulus.Imitating functions that are present in normal hearing may prove to bevery helpful. Advantageously, the present methods and systems allow suchimitations to be more readily achieved.

As a simple example, the Amplitude Relative to Threshold vs. Probabilityof Selection relationship shown by the curve in FIG. 6 may be differentfor each channel, depending on the center frequency of the channel.Differences in the center point of this curve would produce apre-emphasis curve across the spectrum, resulting in a greaterlikelihood of selection for channels with certain center frequencies.Changing the slope of these curves would change the dynamic response ofcertain frequency channels to deviations from the threshold.

To imitate masking effects, the selection of the same channel forstimulation a certain number of times may be used as a control signal toreduce the probability of future selection of the channel. The dynamicsof this masking effect may be easily adjustable by changing theparameters of the algorithm. Cross channel masking effects may beimplemented, for example, by using a control matrix which allowsinformation about the selection history of one channel to be used toaffect other channels.

The preceding description has been presented only to illustrate anddescribe embodiments of the invention. It is not intended to beexhaustive or to limit the invention to any precise form disclosed. Manymodifications and variations are possible in light of the aboveteaching.

1. A stimulation channel selection method for an implantable cochlearstimulation system having a multiplicity of channels, comprising:computing a probability for each channel within the multiplicity ofchannels; and selecting, by a speech processor included within theimplantable cochlear stimulation system, at least one of the channelsfor stimulation during a frame; wherein the selecting of the at leastone of the channels for stimulation during the frame comprises:selecting a channel; obtaining a random number; comparing the randomnumber to the probability of the channel; and selecting the channel forstimulation if the probability of the channel is greater than the randomnumber.
 2. The method of claim 1, wherein the selecting of the channelcomprises randomly selecting a channel which has not previously beenselected for the frame.
 3. The method of claim 1, further comprisingrepeating the selecting of the at least one of the channels forstimulation during the frame until one or more random numbers have beenobtained and compared to corresponding probabilities of each of thechannels within the multiplicity of channels.
 4. The method of claim 1,wherein said implantable neural stimulation system comprises at leastone or more of a spinal cord stimulation system and a deep brainstimulation system.
 5. The method of claim 1, further comprisingdetermining an amplitude for each channel within the multiplicity ofchannels, and wherein the step of computing the probability for eachchannel comprises computing a probability for each channel based on theamplitude of each channel.
 6. The method of claim 5, wherein the step ofdetermining an amplitude for each channel comprises determining anenvelope of each channel.
 7. The method of claim 5, wherein the step ofcomputing a probability for each channel based on the amplitude of eachchannel comprises: determining a number N of channels to be stimulatedduring the frame; summing the amplitudes of the channels to obtain asum; and computing the probability for each channel by dividing theamplitude of each channel by the sum and multiplying the result by thenumber N.
 8. The method of claim 1, further comprising adjusting theprobabilities of the channels based on center frequencies of thechannels.
 9. The method of claim 8, wherein the step of adjusting theprobabilities of the channels based on the center frequencies of thechannels comprises: selecting at least one center frequency to adjust;scaling the probability of the channel with the selected centerfrequency; and normalizing the probabilities of all of the channels.